• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.465-472
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• 2021

In this paper, we present an approach for detection of adverse drug reactions from drug reviews to compensate limitations of the spontaneous adverse drug reactions reporting system. Considering negative reviews usually contain adverse drug reactions, sentiment analysis on drug reviews was performed and extracted negative reviews. After then, MedDRA dictionary and named entity recognition were applied to the negative reviews to detect adverse drug reactions. For the experiment, drug reviews of Celecoxib, Naproxen, and Ibuprofen from 5 drug review sites, and analyzed. Our results showed that detection of adverse drug reactions is able to compensate to limitation of under-reporting in the spontaneous adverse drugs reactions reporting system.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.670-672
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• 2023

본 논문에서는 소셜 미디어 약물 리뷰 데이터로부터 약물 이상 반응을 탐지하는 모델인 FC-BERT 를 기반으로 소셜 네트워크 분석을 활용하여 웹 애플리케이션을 구현하였다. FC-BERT 모델을 거쳐 나온 개체명 인식 결과 중에 같은 의미를 가진 서로 다른 약물 이상 반응 표현들을 MedDRA 부작용 사전을 참고하여 하나의 MedDRA 용어로 표준화하여 매핑했다. 해당 결과에 소셜 네트워크 분석 기법을 적용하여 생성한 상위 15 개의 ADR 동시 출현 그래프를 상위 30 개의 워드 클라우드와 함께 시각화하여 보여주는 웹 애플리케이션을 개발했다. 동시 출현 그래프는 가장 많은 리뷰에서 동시에 나타나는 ADR 쌍을 보여준다. 본 논문에서 제안한 웹 애플리케이션은 사람마다 다르게 나타나는 다양한 약물 이상 반응을 사용자에게 좀 더 접근성이 좋게 제공할 수 있을 것으로 보인다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.549-552
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• 2022

최근 소셜미디어 리뷰 데이터를 활용한 약물 이상 반응 탐지 연구가 활발히 진행되고 있지만, 약물을 복용하기 전 증상과 약물 이상 반응을 구분하지 못한다는 한계가 있다. 본 논문에서는 약물 이상 반응 탐지에서 약물 복용 전의 증상을 구분할 수 있는 Filtering Clinical BERT(FC-BERT) 모델을 제안하였다. FC-BERT 는 약물 복용 전 증상과 다른 약물에 대한 부작용 표현을 제거하기 위해 약물명이 나오기 전 모든 문장을 제거하는 필터링과 약물-부작용 쌍을 추출하는 모델을 사용했다. 성능 평가 실험을 위해 문장에 대한 ADE(Adverse Drug Event) 여부가 들어있는 ADE Corpus V2 데이터를 활용하였고 SPARK NLP 라이브러리에서 제공하는 ADE Pipeline 모델과 비교하여 성능 평가를 실시하였다. 실험 결과 필터링을 활용한 FC-BERT 모델이 기존 모델보다 정확도, 평균 정밀도, 평균 재현율, 평균 F1-score 가 모두 높은 결과를 보여주었다. 본 논문에서 제시한 모델은 기존 연구의 한계점을 보완하여 보다 정확한 약물 부작용 시그널을 탐지하는데 기여할 수 있을 것이다.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.183-192
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• 2009

ADESS(Adverse drug event surveillance system) is the system which distinguishes adverse drug events using adverse drug signals. This system shows superior effectiveness in adverse drug surveillance than current methods such as volunteer reporting or char review. In this study, we built clinical data mart(CDM) for the development of ADESS. This CDM could obtain data reliability by applying data quality management and the most suitable clustering number(n=4) was gained through the reproducibility assessment in unsupervised learning techniques of knowledge discovery. As the result of analysis, by applying the clustering number(N=4) K-means, Kohonen, and two-step clustering models were produced and we confirmed that the K-means algorithm makes the most closest clustering to the result of adverse drug events.

• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.106-114
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• 2009

In this study, we are analysing adverse drug events and proposing a technical structure of "adverse drug event surveillance system" using business intelligence technology, hoping that we can use the system commonly and actively. It is the recent trend to adopt both of electronic review and manual review process to surveil adverse drug events and this study construct CDW applying ETL in BI Technology. As the result of analysis, the data pool included 701 doctors who prescribed and 3059 patients(1528 male, 1531 female), of total 318,222 cases, 2,086cases(0.6%) were suspected as having adverse drug events. And the single type of T.bilirubin> 3mg/dL(ADE type-LabR0005) was the most common(548 among 2085 cases) within the framework of signals.

• Journal of Life Science
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• v.31 no.9
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• pp.849-855
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• 2021

Recently, as nanotechnology has been introduced and used in various fields, the development of new drugs has been accelerating. Nanoparticles have maintained blood drug concentration for extended periods of time with a single administration of the drug. The drug can then be selectively released only at the pathological site, thereby reducing side effects to other non-pathological sites. In addition, nanoparticles can be modified for selective target sites delivery for other specific diseases, with polymers being widely used in the manufacture of these nanoparticles. Poly (D,L-lactic-co-glycolic acid ) (PLGA) is one of the most extensively developed biodegradable polymers. PLGA is widely used in drug delivery for a variety of applications. It has also been approved by the FDA as a drug delivery system and is widely applied in controlled release formulations, such as in gene therapy treatments. PLGA nanoparticles have been developed as delivery systems with high efficiency to specific cell types by using passive and active targeting methods. After the development of a drug delivery system using PLGA nanoparticles, the drug is selectively delivered to the target site, and the effective blood concentration for extended periods of time is optimized according to the disease. In this review paper, we focus on ways to improve cell-specific treatment outcomes by examining the development of astrocyte selective nanoparticles based on PLGA nanomaterials for gene therapy.

• Applied Chemistry for Engineering
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• v.34 no.1
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• pp.1-8
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• 2023

Polyethylenimine (PEI) is a cationic polymer that can bind to negatively charged biomaterials such as nucleic acids through strong electrostatic interactions. Based on these properties, PEI has been used as an efficient drug delivery system for a long time. However, the strong cationic nature of PEI has the problem of causing cytotoxicity by non-specific interaction with anionic biological materials in the cells. In order to overcome these problems, many researchers have developed various types of biocompatible PEI-based materials. In this review, we would like to introduce the recent developments of functional PEI and their applications in biomedical research.

• Journal of Food Hygiene and Safety
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• v.36 no.5
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• pp.363-375
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• 2021

Trends in the developing era to discover and design peptide-based treatments throughout an epidemic infection scenario such as COVID-19 could progress into a more efficient and low-cost therapeutic environment. However, the weakening of proteolysis is one downside of natural peptide drugs. But, peptidomimetics may help resolve this issue. In this review, peptide and peptide-based drug discovery were summarized to target one key entry mechanism of severe coronavirus pulmonary emboli syndrome (SARS-CoV-2), which encompasses the association of the host angiotensin-converting enzyme-2 (ACE2) receptor and viral spike (S) protein. Furthermore, the benefits of proteins, peptides and other possible actions that have been studied for COVID-19 through new peptide-based treatments are discussed in the review. Lastly, an overview of the peptide-based drug therapy environment is comprised of an evolutionary viewpoint, structural properties, operational thresholds, and an explanation of the therapeutic area.

• Journal of the Korean Applied Science and Technology
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• v.29 no.1
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• pp.19-32
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• 2012

Pharmaceutical use accounts for a great part of articles and papers on crosslinking of polymers. Crosslinking of polymers used for tissue engineering and drug delivery respects non-cytotoxicity and in situ gelling. The crosslinking of polymers is aimed not only at the improvement of modulus, chemical resistance, and thermal resistance, but also at endowing them with such functions as metal adsorption, antifouling, and ion exchange via crosslinked segments. Smart polymers responding to environmental change, and cosslinking mediated by light, enzyme, natural compound and in aqueous medium in consideration of environment are being studied. Developing new polymeric materials is essential along with the pharmaceutics aiming at the longevity of 120 years old. Functionalization and property adjustment of polymers through crosslinking will be done more delicately. Hydrogels will be focused on injectable and in situ gel forming. In the coating industry crosslinking system with low non-toxicity and low energy consumption will be developed in consideration of workers and environment.

• Journal of Life Science
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• v.27 no.8
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• pp.958-964
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• 2017

Autophagy plays an important role in cellular homeostasis and survival for cell recycling and various stresses within the cell. Recent studies have shown that autophagy activity modulates the expression of oncogene and tumor suppressor genes, leading to the development or suppression of cancer. Induction of autophagy is involved in preventing cancer development in normal cells and plays an important role in prompting a specific cell death mechanism in cancer cells with damaged cell death function. It is also known that autophagy inhibition increases the therapeutic efficacy by sensitizing cancer cells that are resistant to chemotherapy. However, the role of autophagy has not yet been fully understood in cancer treatment. Oral squamous cell carcinoma accounts for more than 90% of oral cancer and is the sixth most common cancer in the world. The incidence of oral cancer has increased by 50% over the last 20 years and the mortality rate is over 40% within 5 years after the onset. In oral cancers, the role of autophagy are described to look for tumor inhibitory in the early stages of tumor formation, like other cancers, indicating the dual functions involved in tumor cell survival include tumor progression stages. This review summarizes the various roles of autophagy in cancer cells and suggests the possibility of autophagy as a promising target for effective oral cancer therapy.